The 2026 AI Hacker Stack
After fine-tuning 40+ models this year, here's the stack that compounds.
Agent architectures, prompt engineering deep-dives, jailbreak research, and operational AI tactics. From researchers who actually run experiments — not vibes.
Read the cornerstone posts Browse categories8 deep verticals — comparison reviews, tutorials, listicles built on real experience.
Agent architectures, frameworks, autonomous systems.
// promptsPrompt patterns, jailbreaks, red-team techniques.
// modelsClaude, GPT, Gemini, Llama, Qwen — real benchmarks.
// fine-tuningLoRA, QLoRA, full fine-tunes — what actually works.
// ragVector DBs, retrieval architectures, production RAG.
// inferencevLLM, SGLang, llama.cpp — running models in production.
// local-aiOllama, LM Studio, GGUF — AI on your hardware.
// securityPrompt injection, red teaming, model security research.
Long-form pieces on the operational decisions that actually matter in 2026.
After fine-tuning 40+ models this year, here's the stack that compounds.
LangChain, CrewAI, AutoGen — why the 200-line custom loop wins.
Red-team research on Claude, GPT-5, Gemini — the patterns that still work.
After deploying RAG at 6 companies, here's what works and what's theater.
Gemma 3 27B on a 4090. The local-AI playbook that ships.
200 lines of custom code beats the framework. Every time.